Data or Anecdotes; Which Is More Important?

Data seems to consume our lives today but what do we really know about data? Why is data important? What kind of data should we be using to make intelligent business decisions? How far has the world of data come from? Why am I asking so many damn questions right now? Listen in as guest Andrew Hamada, CEO of Reason Automation, schools us on data and why it's useful in our lives but why it's also not THE most important piece of information out there.

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Michael Maher  00:00

Hello, everybody. This is The Longer Game where we talk about retail, reimagined, all things retail, and we like to have a good time doing it. Today I have with me the CEO of Reason Automation, Andrew Hamada, I'm guessing by the last name, it's a Japanese descent. Don't ask me what I majored in in college, because you might be embarrassed to find out. But I welcome to the show, Andrew. Tell us what tell us what's going on in your world right now.

Andrew Hamada  00:28

Thanks for having me, Michael. First nailed it. Japanese descent, which is incredible, because almost nobody gets it on the first try. So,

Michael Maher  00:36

It's because I took Japanese for like, eight years. I'm not fluent at all, because I have no one to speak it with. The only people I could try to get to speak with it with was when I worked in the mall, here, and I would try and speak to like Japanese girls, and they would always just like laugh and go, “Oh, that's so cute.” Speaking English, and I'm like, I'm trying to speak Japanese. To help me my major in college was Asian Studies.

Andrew Hamada  01:01

Gotcha. Yeah. And we're, they're all probably waiting to practice their English on you, so.

Michael Maher  01:05

Right? Yeah. So it was, it worked out both ways, I guess.

Andrew Hamada  01:08

Yep. Cool. Well, that's a fun detail to know about you, sir. The, 

Michael Maher  01:13

I'll let you know,  when I use the degree.

Andrew Hamada  01:16

Yeah, please do. So yeah, as you mentioned, I'm co-founder and CEO of Reason Automation. In plain English, we help brands and agencies get their data, Amazon data out of Amazon systems and into whatever tool or software that they're already using. So that they can do analysis, whether that's just regular weekly business reporting, or more substantial analysis for things like forecasting, back of the office accounting and reconciliation, or even deeper customer and marketing analysis. My co-founders and I are have been in the industry for quite a while. I was at Amazon for about seven years. In very,

Michael Maher  01:54

That's a long, that's a long time. It really is, isn't it?

Andrew Hamada  01:58

It's, it's longer than average. Yes. And just to be self-critical about it. I didn't do it all in one go. I had to take a break in the middle. There were nights - come back. 

Michael Maher  02:06

Okay. That makes me feel better. Personally, makes me personally feel better.

Andrew Hamada  02:13

Yeah. Whereas in my co-founders were the same way. A lot of them have multiple tours. But since then, we

Michael Maher  02:18

multiple tours. Oh, I like how that sounds. You guys are going into war over there. You know, I actually had Tyler Wallace on the program. 

Andrew Hamada  02:27

Oh, yeah. 

Michael Maher  02:28

Yeah, I'm sure you've known him only because he was there for seven years in a row. And when he looked back at the end, I know that there was some kind of like grandpa alert or senior alert for people who had been there the longest, and he was like, 90, like older than 90%, or just had been there longer than 97% of the people. So I mean, honestly, that's just I think it's a testament to the fortitude, the mental fortitude that you have to have in that environment. That's so fast-paced. And, you know, very, what's the word I'm looking for? It's very. I don't know, I don't want to say cutthroat but it's it's very. what's what, there's a word that I'm just blanking on? Yeah, it's competitive. It's very competitive. 

Andrew Hamada  03:13

Yeah, it was even maybe a little aggressively competitive. Yeah. You know, it's and I imagined that Amazon is not unique in the world, like a company in this way. 

Michael Maher  03:22

Oh, yeah. 

Andrew Hamada  03:24

But they hire a bunch of very smart people, very talented people, give them a lot of responsibility and make sure that those responsibilities overlap. And so you have a lot of natural points of conflict, which is good for the business, helps generate the best ideas helps ensure you have coverage of things and that there's no single points of failure. But it does mean that you know, a lot of folks who are very sure that they've got the best idea, because they're very used to having the best idea are suddenly going to be in a room with five other people who think,

Michael Maher  03:52

who might have a much better idea than you. But you know what, that is a Rule of Life, to put yourself in environments where the people around you are better. Now, you have to also realize that if you don't raise your level of acumen, the people around you are going to want to move to be in a room with someone else, that's better. But if you don't, I was just talking about this with a gentleman that I mentor earlier today. And I just said, if you're always in a place where things just work easily for you, you don't necessarily know why it's working. You just know that it is, when you find out when something's failing, you can say okay, here's why this didn't work. Now, I know what to do in the future. Now, I'm not saying go out and intentionally fail. You know, maybe Malcolm Gladwell would say differently, I don't know. But he's not coming on my podcast. So he doesn't get to talk about that. I get to determine what we say. But you don't learn a ton from failure. I mean, sorry, you don't learn a ton from success. I believe you learn a lot from failure. So when you are getting told you're wrong, but here's why you're wrong. You actually learn a lot more so if you can actually get yourself in a room with other people understand why you're wrong and grow in that regard, it's probably one of the best places that you can be.

Andrew Hamada  05:05

I think you hit the nail on the head there. And that's generally how I think of my time at Amazon is it was like the best job that I probably don't want to have again.

Michael Maher  05:14

Yeah, that's a good way of looking at it. Because you, you, you learn so much in that time period. And looking back, you don't regret being there. But you're like, Okay, I've, I've moved past that. And I'm in a place now where I'm, I'm an entrepreneur, I'm a CEO, co-founder of a company, and looking at things in a different guard. But that helped frame your perspective moving forward.

Andrew Hamada  05:37

Exactly. Not to continue the military analogies, but a lot of folks liken it to boot camp, where it's you go in, and you have all these preconceived notions of what you're there to do and what you're what you can accomplish and what your skill sets are. And then after, you know, whatever it is eight or 10 weeks, you've had the crap beaten out of you physically and mentally and emotionally, but you've also been rebuilt in a very, very specific way. And most of the folks that I know, who have gone through it have a very similar perspective on it, where they wouldn't take it back, it judged who they were as a person in many, many ways. But if they had, if they got the offer to go back there tomorrow, they'd say, Yes, somebody else can take that.

Michael Maher  06:17

I'm good. But also, you know, you know what to expect, you don't know what to expect, you're a little bit more bright-eyed and bushy-tailed, and you're like, I can take this on me, honestly, maybe you need, there's a level of ignorance going into that. Maybe you need that, to be able to go through something. I mean, my dad is a physician, and he said that, looking back, he probably would cuz he started out as a biochemist. And when he was 35, went back to med school with three young kids. So that was, yeah, pretty crazy. He's like, looking back. Now, I don't think I would have done that. But he didn't even know any better. So he did it. And he ended up, you know, being in a place where I think he really felt more fulfilled and was more passionate because of that patient interaction, as opposed to, you know, just being more or clinical. But who cares about my dad? He's not on the podcast, either. Why am I mentioning all these people aren't here. So you, Andrew, you mentioned, you mentioned something about getting data from Amazon, into reporting for people? Why is that even important?

Andrew Hamada  07:21

Hmm, good question. So I think that the, the growth of eCommerce over the past 20-25 years has created data where none existed previously, if you think back to before people could buy things on the internet, and we could track every click and purchase and whatnot. Folks, were largely making guesses about what products to sell, how much to buy, where to stock it, etc, you've got some signals from like aggregate purchasing, and looking at the total volume that would go through a store over time, but your ability to understand at any level of granularity, what those people are doing, how those sales were generated in the first place was, was very difficult. And the example I love to give my team is that when I was first learning, marketing, the way that you measured the performance of a promotional campaign was you needed to include some kind of coupon or promo redemption code that they would take an action on. Otherwise, you would literally never know, if it was just a 20%, flat off sale, and anybody that comes into the store can buy something and receive that discount, then you have no way of attributing whether or not that promotion had an incremental effect, where the,

Michael Maher  08:30

*inaudible* the archaic method of measuring stuff. When you, when we look at where we're at now, but back then it was it was all we really had. Because the idea I think of data analytics was, it wasn't like that. When I think about marketing, advertising, all that kind of stuff. There's a lot of subjectivity to it, I think back to the planes, trains and automobiles movie, or Steve Martin is in that initial conference room. I don't know if you've seen that movie or not. I only saw because my wife introduced me to it. But it's a bunch of guys sitting around a big, you know, high rise in, I think it's in New York. Yeah, cuz he's trying to get back to Chicago. But he's in New York, and he's in this big conference room with this big wagon. This guy's looking at this, like cosmetics campaign or something like, you know, he has, he has no clue what he's doing. He just happens to be well paid and is sitting in this, you know, CEO position, whatever the case might be, but he's looking at this stuff. And he's just like, he just keeps looking at it. And Steve Martin and this other guy there and in the shower, just kind of like waiting for him to make a decision. 

Andrew Hamada  09:35

Right. 

Michael Maher  09:36

Okay, this is this, everything has come down to this. We put all this effort into what we're going to do, and we're just waiting for this one dude, to just say, I think this is the right thing. And sometimes there are people like that, that can do that. But it's probably not majority people,

Andrew Hamada  09:51

Right? Certainly not me. Yeah, so for folks like myself, who don't have that amazing ability.

Michael Maher  09:59

Or just got put in the position. 

Andrew Hamada  10:01

Right? Exactly, you just sort of found yourself *inaudible* in that role. And that happens to be part of your job now, fast forward 20 years, and now we actually have the ability to answer those questions with data and the data exists. And over time, folks, as folks realize that the data exists, are our willingness to make decisions without it decreases at the same pace. And so now in the modern era, the you know, huge number of people that are operating in retail, whether it's eCommerce or not understand the power of making a data-driven decision, whether it's at the individual customer level, or thinking about strategy for your overarching business, or even thinking about an individual's store. And so when you think about why that's so critical to get data out of Amazon systems and into whatever systems that brands and our customers are using, it's a few reasons number one, because of the power of the data that I just described. Number two, because most businesses don't just sell on Amazon, Amazon might be, you know, 50% of their business, it might be 5%. But either, 

Michael Maher  11:05

or should they, I would argue, which is I as much as I love Amazon. And that's the core of what my agency does, you need to be omnichannel.

Andrew Hamada  11:14

Exactly. And for any number of reasons that we could spend probably another hour and a half talking about, but

Michael Maher  11:20

You'll also come back man, there'll be season two, season three, hopefully, so. 

Andrew Hamada  11:24

Sold. But so if you're operating in, you know, say you're in Walmart, Target, eBay, your own direct to consumer channel, and your website, etc. And you have a bunch of data at Amazon, then there's no way for you to you're not interested in just reporting on Amazon or looking at reports in Seller Central, you want that data to become part of your entire picture of your business so that you can understand Amazon as part of your entire omnichannel strategy. And then the third, and I think the most important reason why it's so important to get the data out of Amazon systems is Amazon has way more data available than almost any other retailer or eCommerce platform. Around today, Walmart is making a lot of strides, but they're still playing catch up. And everyone else is in kind of the Stone Age versus where Amazon is because they just didn't grow up with data as part of their DNA. And so what a lot of our customers are doing is using insights from their Amazon business and applying them to other channels. And the only way that they can do that is by getting it out of Amazon systems and combining and transforming it with their own insights and their own data. A specific example would be Amazon categorization of products is a little crazy, and it likes to change. And it doesn't necessarily align with the way any manufacturer thinks of their own product categorization. So

Michael Maher  12:43

That's because Amazon's looking at it from a consumer perspective.

Andrew Hamada  12:46

Exactly. And so that's valuable. But it's also valuable for you to be able to manage and analyze your, your sales performance through the lenses that you use internally. And the only way to do that is to be able to pull the data out Amazon, transform it and then analyze it however you want.

Michael Maher  13:01

I've heard that, you know, I heard the argument. Maybe probably three to five years ago, it was a little bit more common. And it was that Amazon doesn't give you enough data to make decisions on the platform. And I always thought that was weird, because even if you felt like they didn't give you, you know, they're not giving you incremental breakdowns of every time you lower your CPC, what is that incremental costs decrease for the month or whatever the case might be like, they're not breaking things down on a super micro level. But if you can see how many sessions are going to your product, and what your conversion rate looks like, you can look at your product detail page and say, Hmm, what is the standard one? And what are other people in the category doing that seem to be successful? That's a lot of data right there. And I hear people say, data, and we're talking about this earlier, but data is its numbers, its words, letters, signals, it's anything that helps us to identify and measure something and put into context. And why something like a search and report on Amazon is so crucial, I believe, to really getting insight into what people are doing that Amazon is, you're not just you might have an idea of what a keyword people are searching is going to be. But when you actually see the actual search term that was revolutionary for me, not just looking at keywords, but looking at the search terms and saying, Oh, I thought it was black pen, but people are looking at a shiny black pen. I didn't realize that that's not something I was thinking of. And that goes back to that old model of guessing Hey, I think this is going to be the right thing. And then you can actually look at what consumers are searching and say oh Well, we thought it was this, but we can now adjust and align more with them so that we get more their attention. I think also you could, there's an opportunity for people to say, we don't have a shiny black pen, but more people are searching for that. So we're gonna put that in front of people. 

Andrew Hamada  15:14

Exactly. 

Michael Maher  15:15

I don't know what I would call that, data manipulation, I would just say, it's poor strategy, maybe, you know, because you're, you're, you're confusing the consumer. And ultimately, they're gonna be frustrated by you know, not getting what it is that they're looking for. Unless you just have this incredibly, you're the anti shiny pen, you're the most matte pen on the market, and you want to change people's idea on what pen fashion. And I don't know how detailed you want to want to jump into that. But it's important because I see data really, as this story. There's all these, you know, different, essentially, hieroglyphics, what is it? What is that telling us when someone's searching for a shiny black pen, as opposed to just a black pen? What does that mean is that the attributes are more important than the item itself? How often are people clicking on this compared to other keywords? And is what is why are people clicking? So there's, there's all this information there. And to me, it's like there's a story there. When I look at when a product is being searched on Amazon organically or even shown in an advertisement, I look at it as this conversation. So the search engine sees this product that's getting a lot more sales than normal, it's really high sales velocity, oh, well, this might be more interesting to consumers, and maybe we should put it higher up. And I know, this is all stuff that's being, you know, done in nanoseconds. But that's essentially what's happening is, hey, we're seeing all these different things happen. What do we feel like are the most important and, and what are our objectives and goals? And then let's, let's take what the data that we have, and put that in front of people test it, which I think is a big part of being a brand today, but also in on Amazon specifically. There's, their strategy that's involved their skill that's involved, but a lot of it is, hey, we think this is gonna work. Let's experiment. Let's test it. Let's see what actually works. And then let's go from there.

Andrew Hamada  17:18

Yep. And the appetite to do that only exists because we have the data. And nobody says, let's test this, if they can't measure the results, they say we need to get this right in the first place. And there's no testing, we're just going to make the best possible bet that we can. 

Michael Maher  17:33

Right. I think one of the interesting things too about data and this trend towards data is there becomes this, I believe, an incongruence between what people talk about and what they actually do. I've had people argue about data with me. And I know that Mark Twain said, you know, there's three things I don't know the exact quote, but he's like, there are only three terrible things in the world lies, damned lies, and statistics. My, my wife was not a fan of statistics in college, although she did have to take it. That's another story. But you know, you can manipulate data to look a certain way. You know, wow, look at this crazy growth that's happened. And you've cut off the, you know, the top part of these bar graphs to show Wow, it's jumped up. Incredible. But then when you look down at the base, like, oh, it's actually been, you know, the same for a while. So we know that you can manipulate data. It's not that you're changing the data. It's basically that you're, it's like a kaleidoscope. You're just saying, Okay, well, let's look at it this way. Let's look at it this way. Oh, well, pink is a better color. Let's look at it and think and like Well, no, actually I like red better. Okay, well, who cares? I got a black and white kaleidoscope. So I didn't even get to have the choice between pink and red. So be happy with what you get people. But, when you look at data people are you're talking about data, people are saying, oh, let's be data-focused, let's be data-oriented. But I still see people making a lot of decisions that and if you've got a decision that you feel like you need to go through, get on cool, but people are still making decisions or arguing with data, because they don't like it. How do you deal with that?

Andrew Hamada  19:26

I mean, there, you can tell by my deep sigh This is a problem that I'm intimately familiar with.

Michael Maher  19:32

Why do people argue with data? Andrew, tell me more about that.

Andrew Hamada  19:37

I mean, I won't go into all the psychological reasons why I'm here for a while. Yeah, yeah, there's tons of reasons why the human mind does what it does, and I don't understand all of them. And, you know, particularly as you get down the path of things like logical fallacies like I we'd all go, we'd all fall asleep in a minute here. So I won't go there. But, what I think in general it comes down to is, number one, people just trust their own instincts. And they trust their own lived experience, whether or not that's databased. And it's extremely difficult for anyone to convince another human being away from their lived experience, whether they have data or not. And you can see this over and over and over again with statistics, where folks, oftentimes, even faced with like, really obvious probability metrics will still believe that they can, like outdo, or those probabilities, or they won't apply to them for whatever reason. The most obvious example of this in my universe is I gamble. I go to Vegas and I play, okay, I play I play games sometimes. And you know, I'm not like a hardcore gambler or anything, I don't go regularly. But in order to participate in that, if you understand data like I do, you have to sort of consciously decide that you're going to ignore the odds.

Michael Maher  20:57

Okay, yeah, you're gonna take it, you're gonna take a risk. Yep. By the way, this playing a Pussycat Doll slot machine in Vegas count is as gambling because that's the extent of the game. *inaudible* show in Vegas for some conference. So you'll allow it, okay. 

Andrew Hamada  21:14

It counts it about I wouldn't say that. It means that you're a gambler. I mean, you know, if you pulled one, 

Michael Maher  21:18

I have gambles, I have gambled. 

Andrew Hamada  21:20

There you go. That's the nuance. But it's exactly that, right? It's we trust our own feelings about what the outcomes are going to be more than even things that we understand rigorously to be true. And one of my all time favorite Jeff Bezos quotes is actually about this exact phenomenon, where I can't remember he was speaking at some wealth conference, and not a major one. So this quote doesn't get floated around a lot. But he said, the thing that I've noticed is that when anecdotes and data disagree, that the anecdotes are usually right. And that was shocking to me from coming from Jeff Bezos. Yeah. And the reason, I sat with this quote for a long time trying to figure out what the heck he meant, and why he's saying this out loud, but making me at Amazon justify everything with data to the right degree.

Michael Maher  22:14

Excuse me, Jeff, hold on, I have a question.

Andrew Hamada  22:17

Exactly right. Like, does this mean I can change my job now? Like, did we just lower the bar? Thanks very much. But I think what he actually means is this, it's less about how do you overcome the barriers with folks who disagree with data and more about how do you take that disagreement and use it as a reflection of your own measurement and reporting systems. And looking at Amazon, the way that he would apply this is Amazon obviously has a ton of data, a ton of instrumentation to measure everything, tons of telemetry to report on that to all the right folks at all the right times, etc. And yet, Jeff, still treats every email sent to jeff@amazon.com as a high escalation, customer service issue. And now this is well known. So you know, there's a whole team that handles it and blah, blah, blah, blah, blah. But back in the day, it was Jeff was still reading all his own emails. And he would literally for those off to folks to say like, Hey, what the hell's wrong here? And the culture of that is that it's Jeff Bezos emailing you, you don't tell him hey, these anecdotes wrong. Here's the data to prove it. You say, here's the data that shows this isn't happening at scale. But we dug into this anyway, to understand why this anecdote occurred in the first place. And here's what we found. And so I thought,

Michael Maher  23:29

Well, this and that, not this or that. 

Andrew Hamada  23:32

Exactly. And so bringing that all the way back around to your original question, is, I think that that's how I've overcome this objection with as many folks as possible is to help them hear that I'm hearing them, and that I understand why they don't agree with the data and to try as best I can to create a version of the world that allows the data and the anecdote to coexist, whether that's because they're not applying exactly the same thing. So I can show that or because hey, actually, you've helped us discover an edge case that doesn't apply broadly to the other data. So we're going to create a mechanism to measure that. But the right answer is still the data driven one. Yeah, yeah. etc.

Michael Maher  24:11

I think that should be on your business card, I create a world where anecdotes and data can align for people, because that's so true. I mean, I'm, you're you're dealing with probably less people saying, well, why is this data this way? And they're just saying, Am I getting the correct data? I know that on a regular basis, when I'm dealing with other humans, when I'm dealing with clients, they might say, well, this thing is this way or this is bad. And I can say I understand. And it for me, it's not about one, it's not about being right. It used to be about being right. I don't care. I have a good friend who always talks about not caring about being right but about getting it right and so that means I'm wrong often but I'm able to say okay, I was wrong here Let's do this the correct way. And here's why it's correct. This other person came up with the idea, I don't care about being the one that has the idea, I'm just able to say, alright, this seems like the right one, let's extract it, let's, let's go forward and move in that direction. But a lot of times, I remember being an account manager for someone that's, you know, selling on Amazon. They're arguing with you about something. And you're like, but this is this way. And, and I'm and I, there are people who I remember having conversations with and looking back now I'm like, it had nothing to do. They just wanted to be listened to enough. And that, like you said that they're hurt, had nothing to do with the fact that the data was correct. It's about you know, for someone who's used to being on Amazon, and not advertising, and now realizing my business is starting to decline, why am I having to pay for sales that I used to get already, it's not about this is just how it is, it's your right, that is how things have been in the past. And yet at the same time, and that was working, but as you can see, based on declining sales, and advertising is now important. And so you are going to have to start you need to make a decision, you can stick with what you're doing, but expect that you're going to continue to see sales decline. So you can still be okay with the decision-making, if you're okay with the consequence that comes good at good or bad. But you could also start investing advertising, realizing it's a cost of business, and that you have to restructure pricing, or you have to look at margins differently. It can't just be, you know, SEO, I remember, I remember being a seller back in, you know, 2011 2012, write the best listing and get pictures that were mostly white, on a white, mostly white background, that was it, that was selling on Amazon, and there are people that were doing, you know, a million dollars on that, which is, which is crazy. And so as soon as advertising came in, I think honestly, yes, it was an additional cost to people. And of course, you know, people look at, I think a lot of times people look at Amazon as like the savior of all eCommerce, or they look at them as the devil. And they've ruined small business, I was actually in on vacation recently in a bookstore. And there was a book that was called "How to resist Amazon". And I think it said and why which is, so I took a picture of that on my phone, I'm like, this will be interesting, I should send this to some people that I work with. And it's all about, you know, talking about why you should resist Amazon and how essentially, they've ruined small business. Well, they've ruined small business, in the sense that they embrace technology that was already there. And they also, at the same time allowed a lot of businesses that are small businesses, that were new kinds of small businesses or small businesses that were willing to adapt to actually grow and be really successful. I almost showed up at a, like a public forum. That was anti Amazon, just to say, Does anybody actually know how many, you know, like small businesses selling on an Amazon? And here's an anecdote, I used to be one of those people. And now I'm helping people that are doing that. So if you don't know, it's, of course, it's from the outside, it's going to look like yeah, it's totally this way. But in reality, it's it's that and it's the fact that the technology was there, they just embraced it.

Andrew Hamada  28:22

Yeah, I mean, I think that when you're talking about something as incredibly significant as eCommerce and as, or as large as a company, like Amazon have capitalized on eCommerce, it's, it's sort of a slightly, it's almost silly to suggest that like it's 100%, negative to small business or 100% positive a small business, like there's going to be puts and takes on across the board here. You know, are there tons of businesses that were, I'm sure put out of business by the existence and growth of Amazon 100%. Or some of those businesses that would have gone out of business, no matter what, because of the growth and shift in eCommerce, 100%. And to your exact point, are there many new businesses that sprang up because they were able to capitalize on that shift to eCommerce? Or because eCommerce allowed them to create a business that they would never have been able to create before? Yeah, absolutely. And so yeah,

Michael Maher  29:13

It's what we call win win win.

Andrew Hamada  29:15

Exactly. So yeah, I really struggle with like the demonization of like really significant platforms or or entire segments of the market. I mean, saying Amazon is bad is like saying eCommerce is bad. You know, it's it just doesn't feel like it's that simple, ever.

Michael Maher  29:29

I mean, if you're, I don't even know. I don't even know how to put a juxtaposition to that. Yeah, I mean, it's, it's, it's kind of insane. To just say something is bad. It's almost like saying a chair is bad. Well, if you want to stand up, and you're a runner, and that's all you do, then yeah, maybe a chair is bad for you. But a chair is also good if you want to relax and have a glass of bourbon or smoke a cigar or take a nap. I don't know. Like there's a lot of reasons why it could be good as well. 

Andrew Hamada  30:00

Right, it's like, you know, are the ,the one that I come back to all the time related to chairs actually is, you know, I, and probably you and everybody else who's working a white collar gig, a huge amount of our keeping healthy is how do we combat the effects of sitting all day? Yeah, constantly. And then you

Michael Maher  30:17

I used to stand in for some reason I was better in my desk is actually a standing desk. For now, right now I'm sitting more, I don't know why, but I'm just kind of going with it.

Andrew Hamada  30:26

Right. And so it's that but you but you're thinking about it, you're sort of that it's a mental battle that you're fighting, right. And you put that to like my first job at McDonald's where I was, you know, in the drive thru, and you're standing for, like, you know, eight hours, with like, maybe a 30 minute break in the middle, and like, I would have killed for a chair. And so just, you know, in that one example, alone, and just my life experience, you can see how it's like really A or B.

Michael Maher  30:51

And that's also why the anecdote is the one that wins, because that's what's more applicable to you in your life.

Andrew Hamada  30:59

Exactly. And at the end of the day, it's it's never a winning strategy. If I had somebody that asked me why, you know, the data is important versus their anecdote or disagrees with the data because of their anecdote. It's never a good strategy to disagree with somebody's lived experience.

Michael Maher  31:14

Right? And what and honestly, what's, what is the point? Yeah, have you disagree with that? And I think there's, you can look at data in a couple different ways. One is the way of saying, you know, well, you know, facts, don't care about your feelings, which is true. But you still also have feelings. And so you could come out from other way and say, Well, this is what I experienced. And so I want everyone to live according to this thing that I experienced. So you can't expect both. But I think one of the things that I've learned in, in becoming a human and hopefully becoming a better human is, I know that there are statistical factors that are out there that say, this is more probable than this, or this is not as likely as you think it is something like, like terrorism. By the way, I read an article on this is I'm not laughing at terrorism, wait till I get to the punch line. I'm, I read an article about Osama Bin Laden, it was like the 10 things that they found nine things they found in his, you know, his compound, and one of them was was video games. Someone wasn't. And it could have been him. We don't know. But someone likes Super Mario Kart, someone liked. Yeah, I know, someone liked a Call of Duty, believe it or not. There are all these video games out there. I just thought that was really funny. But terrorism, the likelihood of it happening is very, very small. But the threat is so outrageous, and seems so random, that it's really scary enough that a whole country would change their entire, you know, airplane traveling system to focus on the very small likelihood of something doing something of something occurring. So it's, it's I think it's the thing I'm seeing is yes, data can be real. And at the same time, you have to be human enough to say, I see that you have this lived experience. And while this may not be the standard, that's terrible, how do we also fix this thing? And honestly, you look at that stuff. In, in, in culture. And when we're looking at all different kinds of things, looking at racial reconciliation, looking at, you know, biases in different areas. There are there might be data that says one thing, but then a lived experience that says this other thing, how to it's not about either, or it's about how do we actually find those things? And like you said, how do we say, Okay, well, data shows this isn't happening at scale. But we also dug into this into that, I think, if more of us said, we're not worried about this as an overarching problem, but it's still an issue, and it's something that's significant. Here's how we fix this thing. And didn't go either or, like I'm so tired of, well, this person said this, and this other person argued and said that, and I feel like what about the majority of people that aren't really on the extremes, but are standing in the middle? When did this become more political and social? I don't know. But I just brought it there. People from extremes that say there's a lot of people that are standing in the middle that are saying, I recognize that something could be this way and this way, and how do we marry those two things together someone's perspective and data?

Andrew Hamada  34:22

Right, exactly. Bring it back to a business example. Because I can't. Yeah, the way,

Michael Maher  34:30

Maybe you should. 

Andrew Hamada  34:32

Maybe the way that I explained this to folks, especially folks who were earlier career is through this concept that I call that I was taught to me as head in the hallway feedback. And as somebody who runs a big data company, it often shocks people that I care about anecdotes as much as I do, but the way that I explained it, especially to college students is you know, imagine that you're in the dorm and you're getting up in the morning and you're trying to decide what shirt to wear. And you put on a shirt that you're pretty sure looks good, but you're not 100 percent positive, you stick your head in the hallway and you ask the first five people that walk by, hey, does this shirt look good? And the first five people look at you and they go, maybe you should change dude. Are you going to say cool and go change your shirt? Are you going to stop and say, Well, that was only five data points? I haven't hit statistical significance yet, I should probably ask another 95 people in order to get a representative. Like, there's a right answer here, you know? Yeah. And the knowing when to trust that immediate head in the hallway type anecdotal feedback versus to seek the data at scale, and how to apply those things side by side, I think is a massive, lifelong lesson for everyone.

Michael Maher  35:39

Let's just end it there. That was a very wise thing to say. And I think that the more wise things that I find out about, it's less about me coming up with them. And about, like, I was thinking about this. I said, I was going to end it. But I was thinking about this earlier when something is real, it's not real. When you recognize it's real. It's been real the whole time when we thought the Earth was flat and realized it was round. Actually, I heard the earth is flat again. So I don't know I could be wrong. But we, we looked at like the Earth had been round the whole time. We just thought it was flat. Right? So didn't become round. It had been round the whole time. So that's something else to consider is there could just be things that we don't know. And as soon as we're able to wrap our heads around, it's like, okay, well, that makes more sense. But I like, I love what you said. Say it again, what was the last thing you said?

Andrew Hamada  36:32

Just the idea that head in the hallway feedback. And knowing when to apply anecdotes versus big data and how those things can exist side by side, I think is one of the bigger challenges that decision-makers and strategic leaders spend their lives tackling.

Michael Maher  36:47

Okay, well, I think we just solved some kind of world issue. Andrew, if people want to find you, where are they going to look? Are they going to look in a pile of data? Are they going to look in a data lake? Are they going to look behind a dumpster full of data? What were people going to look and see?

Andrew Hamada  37:05

Well, if you want to find me, you can find me on LinkedIn, Andrew Hamada or our website for Reason Automation is reasonautomation.com. Typically, if I'm not in one of those places, I'm probably chillin with Oscar the Grouch in a trash can somewhere. But you know, beyond that, no, I, we and 

Michael Maher  37:23

I need to become better friends with you because I'd love to meet Oscar. He seems like he's cranky. But he seems like a funny guy. It's like to me, he's like a benign, Cranky guy. 

Andrew Hamada  37:33

Yeah, you know, the kind of guy that you want around because he's gonna tell you the exact right snarky thing that you need to hear in order to unblock you at the given time. Yeah, I'll be sure to introduce you.

Michael Maher  37:42

You're cool. Thanks, man. I appreciate it. Thanks for coming on. People check out Reason Automation. They've got a really cool platform that's allowing you to take data and turn it into something that's super useful for you in your organization. This has been the retail, reimagined podcast, aka The Longer Game. I forgot the name of my own podcast there for a second. Thanks for joining us people. Talk to you later.

Andrew Hamada  38:05

Thanks.